Impact of Acyclovir on Genital and Plasma HIV‐1 RNA, Genital Herpes Simplex Virus Type 2 DNA, and Ulcer Healing among HIV‐1–Infected African Women with Herpes Ulcers: A Randomized Placebo‐Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Little is known about the impact of episodic treatment of herpes on human immunodeficiency virus type 1 (HIV-1). METHODS: Women from Ghana and the Central African Republic who had genital ulcers were enrolled in a randomized, double-blind, placebo-controlled trial of acyclovir plus antibacterials and were monitored for 28 days. Ulcer etiologies and detection of lesional HIV-1 RNA were determined by polymerase chain reaction (PCR). Cervicovaginal HIV-1 RNA and herpes simplex virus type 2 (HSV-2) DNA and plasma HIV-1 RNA were quantitated by real-time PCR. Primary analyses included 118 HIV-1-infected women with HSV-2 ulcers (54 of whom were given acyclovir and 64 of whom were given placebo). RESULTS: Acyclovir had little impact on (1) detection of cervicovaginal HIV-1 RNA (risk ratio [RR], 0.96; 95% confidence interval [CI], 0.8-1.2) at day 7 of treatment, (2) the mean cervicovaginal HIV-1 RNA load (-0.06 log(10) copies/mL; 95% CI, -0.4 to 0.3 log(10) copies/mL) at day 7 of treatment, or (3) the plasma HIV-1 RNA load (+0.09 log(10) copies/mL; 95% CI, -0.1 to 0.3 log(10) copies/mL) at day 14 of treatment. At day 7, women receiving acyclovir were less likely to have detectable lesional HIV-1 RNA (RR, 0.70; 95% CI, 0.4-1.2) or cervicovaginal HSV-2 DNA (RR, 0.69; 95% CI, 0.4-1.3), had a lower quantity of HSV-2 DNA (-0.99 log(10) copies/mL; 95% CI, -1.8 to -0.2 log(10) copies/mL), and were more likely to have a healed ulcer (RR, 1.26; 95% CI, 0.9-1.9). CONCLUSION: Episodic therapy for herpes reduced the quantity of cervicovaginal HSV-2 DNA and slightly improved ulcer healing, but it did not decrease genital and plasma HIV-1 RNA loads. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT00158483 .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".